الفهرس 
CHAPTER 1Only 14 pages are availabe for public view
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Abstract
Recently, the integration of wind energy into electrical energy systems has increased considerably due to the economic and environmental benefits relative to conventional energy sources. However, because of the uncertainty and intermittent nature of wind energy output, large-scale wind energy integration has an obvious impact on the performance and stability of the power systems. Several factors limit the increase of the penetration level of wind energy, particularly in the deregulated systems. One such substantial factor that should be precisely estimated is available transfer capability (ATC) to ensure a reliable transfer of renewable energy to remote regions. ATC is the additional transfer capability that can be transferred through a transmission line above the committed uses without violation of operational limits as defined by the North American Electric Reliability Council (NERC).
This thesis proposes an ATC assessment approach in an intraday market that would enable wind energy participants to raise their level of integration without exposing them to high risk. The presented methodology allows the transmission system operator (TSO) to assess ATC near to the real state while considering voltage stability concerns as well as the uncertainties of the forecasted load and wind power. The proposed formulation is designed so that the existing VAR sources are appropriately exploited during the ATC assessment to maximize its anticipated value and boost the transaction between various zones. To alleviate the complexity of analyzing N-1 contingencies in the ATC estimation, a linear sensitivity technique is applied for ranking the most severe contingencies to be examined carefully.
A two-level hybrid algorithm using the primal-dual interior point method (PDIPM) and an improved grey wolf optimizer (IGWO) is suggested for solving the problem. The performance of the proposed approach has been evaluated by its application on IEEE 30- reliability test system (RTS). The outcomes confirm the viability of the proposed approach for optimizing ATC value for various transactions through the best use of installed VAR devices, considering different locations of wind farms. The obtained findings also demonstrate the effectiveness of the suggested method for determining the most severe contingency associated with each scenario under consideration. Moreover, multi-objective grey wolf optimizer (MOGWO) is applied to solve the multi-objective problem of maximizing ATC and minimizing generation cost as well as mitigating emission cost considering the reactive capability curve of doubly fed induction generator (DFIG) of wind turbine (WT).